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- W72097679 abstract "This chapter investigates the underlying volatility process in earthquake series, explosive series, high-frequency financial data, and financial indices and examines the applicability of a range of GARCH specifications for modeling volatility of these series to identify similarities and differences in the volatility structure. The chapter reviews short memory processes (ARMA and GARCH models) and long memory processes (ARFIMA, ARFIMA-GARCH, and FIGARCH), respectively. It present methods for detecting and estimating long memory processes such as ADF test, KPSS test, and Whittle approximation. The chapter discusses some of the methods that are used to test and estimate long memory parameter. Whittle methodology gives approximate maximum-likelihood estimates of the long memory paramaters based on the calculation of the periodogram by means of the fast Fourier transform (FFT) and the use of the Whittle approximation of the Gaussian log-likelihood function. The chapter discusses the data and empirical results." @default.
- W72097679 created "2016-06-24" @default.
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- W72097679 date "2016-04-08" @default.
- W72097679 modified "2023-10-17" @default.
- W72097679 title "Study of Volatility Structures in Geophysics and Finance Using Garch Models" @default.
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- W72097679 doi "https://doi.org/10.1002/9781118593486.ch10" @default.
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